• Title/Summary/Keyword: 표적기술

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The Effectiveness Analysis of Multistatic Sonar Network Via Detection Peformance (표적탐지성능을 이용한 다중상태 소나의 효과도 분석)

  • Jang, Jae-Hoon;Ku, Bon-Hwa;Hong, Woo-Young;Kim, In-Ik;Ko, Han-Seok
    • Journal of the Korea Institute of Military Science and Technology
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    • v.9 no.1 s.24
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    • pp.24-32
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    • 2006
  • This paper is to analyze the effectiveness of multistatic sonar network based on detection performance. The multistatic sonar network is a distributed detection system that places a source and multi-receivers apart. So it needs a detection technique that relates to decision rule and optimization of sonar system to improve the detection performance. For this we propose a data fusion procedure using Bayesian decision and optimal sensor arrangement by optimizing a bistatic sonar. Also, to analyze the detection performance effectively, we propose the environmental model that simulates a propagation loss and target strength suitable for multistatic sonar networks in real surroundings. The effectiveness analysis on the multistatic sonar network confirms itself as a promising tool for effective allocation of detection resources in multistatic sonar system.

Sensor Node Acoustic Signal Processing in Wireless Sensor Network using Lifting Scheme Wavelet (무선 센서 네트워크에서 Lifting Scheme Wavelet을 이용한 센서 노드 음향 신호 처리)

  • Cha, Dae-Hyun;Lee, Tae-Young;Hong, Jin-Keun;Han, Kun-Hui;Hwang, Chan-Sik
    • Proceedings of the KAIS Fall Conference
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    • 2008.11a
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    • pp.236-239
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    • 2008
  • 무선 센서 네트워크에서 센서 노드는 그 목적에 따라 다양한 신호처리 기능을 가져야 한다. 센서 노드의 에너지 제약과 통신 대역폭 제한은 센서 노드에서의 가벼운 신호처리 기법을 필요로 한다. 일반적인 센서 노드에서의 신호처리 기법은 센서 노드에 수신된 신호를 잡음제거 등의 전처리를 수행하고, 에너지를 계산하여 표적의 위치를 탐지하고 기지국에서의 위치추정 및 식별을 위하여 특징 추출하거나 압축하여 전송하는 등의 방법으로 구성된다. 이러한 센서 노드에서 필수적인 신호처리 기법들은 에너지 효율적인 신호처리 기법은 무선 센서 네트워크의 생존 시간과 표적 탐지 및 식별이라는 목적에 대한 성능에 큰 영향을 끼치게 된다. 본 논문에서는 무선 센서 네트워크에서 센서 노드의 필수적인 신호처리를 Lifting scheme wavelet 방법을 이용하여 센서 노드에서 에너지 효율적인 신호처리 기법을 제안한다.

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Three-dimensional Distortion-tolerant Object Recognition using Computational Integral Imaging and Statistical Pattern Analysis (집적 영상의 복원과 통계적 패턴분석을 이용한 왜곡에 강인한 3차원 물체 인식)

  • Yeom, Seok-Won;Lee, Dong-Su;Son, Jung-Young;Kim, Shin-Hwan
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.10B
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    • pp.1111-1116
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    • 2009
  • In this paper, we discuss distortion-tolerant pattern recognition using computational integral imaging reconstruction. Three-dimensional object information is captured by the integral imaging pick-up process. The captured information is numerically reconstructed at arbitrary depth-levels by averaging the corresponding pixels. We apply Fisher linear discriminant analysis combined with principal component analysis to computationally reconstructed images for the distortion-tolerant recognition. Fisher linear discriminant analysis maximizes the discrimination capability between classes and principal component analysis reduces the dimensionality with the minimum mean squared errors between the original and the restored images. The presented methods provide the promising results for the classification of out-of-plane rotated objects.

Development of Collision Avoidance System based on TCAS II for Smart UAV (TCAS II를 이용한 스마트무인기용 충돌회피시스템 개발)

  • Lee, Hyeon-Cheol;Kim, Seung-Ju
    • Aerospace Engineering and Technology
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    • v.5 no.2
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    • pp.248-257
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    • 2006
  • There will come someday when UAUs can fly into the airspace of manned aircraft in the near future because of the increasing number of operational UAUs together with technologies development. Since pilots of UAVs are on the gound, the equipment for sensing and avoiding obstacles in front is indispensable. In this paper, we analyze functions and interfaces of TCAS II, a collision avoidance device for manned aircraft, then find out whether it is suitable for the collision avoidance device for UAV and problems associated with it, if any. It turns out to be that the onboard directional antenna of TCAS II does not provide a precise directional information, and that the TCAS II is not assumed to be installed alone, but used as supplementary with other device which provides the better precision.

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Human Operator Modeling and Input Command Shaping Design for Manual Target Tracking System (수동표적추적장치의 휴먼운용자 모델링 및 입력명령형성기 설계)

  • Lee, Seok-Jae;Lyou, Joon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.10 no.2
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    • pp.21-30
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    • 2007
  • A practical method to design the input shaping which generates control command is proposed in this paper, We suggest an experimental technique considering human operator's target tracking error to improve aiming accuracy which significantly affects hit probability. It is known that stabilization performance is one of the most important factors for ground combat vehicle system. In particular, stabilization error of the manual target tracking system mounted on moving vehicle directly affects hit probability. To reduce this error, we applied input command shaping method using preprocessing filtering and functional curve fitting. First of all, we construct the human operator model to consider effects of human operator on our system. Input shaping curve is divided into several regions to get rid of the above problems and to improve the system performance. At example design part, we chose three steps of functional command curve and determine the parameters of the function by the proposed design method. In order to verify the proposed design method, we carried out the experiments with real plant of a fighting vehicle.

Study of Target Tracking Algorithm using iterative Joint Integrated Probabilistic Data Association in Low SNR Multi-Target Environments (낮은 SNR 다중 표적 환경에서의 iterative Joint Integrated Probabilistic Data Association을 이용한 표적추적 알고리즘 연구)

  • Kim, Hyung-June;Song, Taek-Lyul
    • Journal of the Korea Institute of Military Science and Technology
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    • v.23 no.3
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    • pp.204-212
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    • 2020
  • For general target tracking works by receiving a set of measurements from sensor. However, if the SNR(Signal to Noise Ratio) is low due to small RCS(Radar Cross Section), caused by remote small targets, the target's information can be lost during signal processing. TBD(Track Before Detect) is an algorithm that performs target tracking without threshold for detection. That is, all sensor data is sent to the tracking system, which prevents the loss of the target's information by thresholding the signal intensity. On the other hand, using all sensor data inevitably leads to computational problems that can severely limit the application. In this paper, we propose an iterative Joint Integrated Probabilistic Data Association as a practical target tracking technique suitable for a low SNR multi-target environment with real time operation capability, and verify its performance through simulation studies.

A Study on Detection of Underwater Ferromagnetic Target for Harbor Surveillance (항만 감시를 위한 수중 강자성 표적 탐지에 관한 연구)

  • Kim, Minho;Joo, Unggul;Lim, Changsum;Yoon, Sanggi;Moon, Sangtaeck
    • Journal of the Korea Institute of Military Science and Technology
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    • v.18 no.4
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    • pp.350-357
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    • 2015
  • Many countries have been developing and operating an underwater surveillance system in order to protect their oceanic environment from infiltrating hostile marine forces which intend to lay mines, conduct reconnaissance and destroy friendly ships anchored at the harbor. One of the most efficient methods to detect unidentified submarine approaching harbor is sensing variation of magnetism of target by magnetic sensors. This measurement system has an advantage of high possibility of detection and low probability of false alarm, compared to acoustic sensors, although it has relatively decreased detection range. The contents of this paper mainly cover the analysis of possible effectiveness of magnetic sensors. First of all, environmental characteristics of surveillance area and magnetic information of simulated targets has been analyzed. Subsequently, a signal processing method of separating target from geomagnetic field and methods of estimating target location has been proposed.

Mean Field Game based Reinforcement Learning for Weapon-Target Assignment (평균 필드 게임 기반의 강화학습을 통한 무기-표적 할당)

  • Shin, Min Kyu;Park, Soon-Seo;Lee, Daniel;Choi, Han-Lim
    • Journal of the Korea Institute of Military Science and Technology
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    • v.23 no.4
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    • pp.337-345
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    • 2020
  • The Weapon-Target Assignment(WTA) problem can be formulated as an optimization problem that minimize the threat of targets. Existing methods consider the trade-off between optimality and execution time to meet the various mission objectives. We propose a multi-agent reinforcement learning algorithm for WTA based on mean field game to solve the problem in real-time with nearly optimal accuracy. Mean field game is a recent method introduced to relieve the curse of dimensionality in multi-agent learning algorithm. In addition, previous reinforcement learning models for WTA generally do not consider weapon interference, which may be critical in real world operations. Therefore, we modify the reward function to discourage the crossing of weapon trajectories. The feasibility of the proposed method was verified through simulation of a WTA problem with multiple targets in realtime and the proposed algorithm can assign the weapons to all targets without crossing trajectories of weapons.

Method for Similarity Assessment Between Target SAR Images Using Scattering Center Information (산란점 정보를 이용한 표적 SAR 영상 간 유사도 평가기법)

  • Park, Ji-Hoon;Lim, Ho
    • Journal of the Korea Institute of Military Science and Technology
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    • v.22 no.6
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    • pp.735-744
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    • 2019
  • One of the key factors for recognition performance in the automatic target recognition for synthetic aperture radar imagery(SAR-ATR) system is reliability of the SAR target database. To achieve optimal performance, the database should be constructed using the images obtained under the same operating condition as the SAR sensor. However, it is impractical to have the extensive set of real-world SAR images, and thus those from the electro magnetic prediction tool with 3-D CAD models are suggested as an alternative where their reliability can be always questionable. In this paper, a method for similarity assessment between target SAR images is presented inspired by the fact that a target SAR image is mainly characterized by the features of scattering centers. The method is demonstrated using a variety of examples and quantitatively measures the similarity related to reliability. Its assessment performance is further compared with that of the existing metric, structural similarity(SSIM).

Position Estimation of Underwater Target Using Proximity Sensor with Bearing Information (근접 센서의 방위정보를 이용한 수중표적 예상위치 추정 기법)

  • Choi, Young-Doo;Kim, Jung-Hoon;Yoon, Kyung-Sik;Seo, Ik-Su;Lee, Dong-Hun;Lee, Kyun-Kyung
    • Journal of the Korea Institute of Military Science and Technology
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    • v.17 no.4
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    • pp.422-429
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    • 2014
  • Proximity sensor networks are aimed at estimation kinematic state of target using estimated position of the target by each sensor node or target parameter. To analyze the kinematic state of target, traditional approaches require detections on multiple sensors, very large number of sensors to achieve acceptable performance. In this paper, we propose a novel method which can estimate predicted position of the underwater target using minimum proximity sensor with bearing information to this problem. The proposed algorithm was verified performance through simulation.